Dependable systems for Sentient Computing

Abstract

Computers and electronic devices are continuing to proliferate
throughout our lives. Sentient Computing systems aim to reduce the time
and effort required to interact with these devices by composing them
into systems which fade into the background of the user’s perception.
Failures are a significant problem in this scenario because their
occurrence will pull the system into the foreground as the user attempts
to discover and understand the fault. However, attempting to exist and
interact with users in a real, unpredictable, physical environment
rather than a well-constrained virtual environment makes failures
inevitable.

This dissertation describes a study of dependability. A dependable
system permits applications to discover the extent of failures and to
adapt accordingly such that their continued behaviour is intuitive to
users of the system.

Cantag, a reliable marker-based machine-vision system, has been
developed to aid the investigation of dependability. The description of
Cantag includes specific contributions for marker tracking such as
rotationally invariant coding schemes and reliable back-projection for
circular tags. An analysis of Cantag’s theoretical performance is
presented and compared to its real-world behaviour. This analysis is
used to develop optimised tag designs and performance metrics. The use
of validation is proposed to permit runtime calculation of observable
metrics and verification of system components. Formal proof methods are
combined with a logical validation framework to show the validity of
performance optimisations.